Tootfinder

from my link log —
Emulating aarch64 in software using JIT compilation and Rust.
https://pitsidianak.is/blog/posts/2025-08-25_emulating_aarch64_in_software_using_JIT_compilation.html
saved 2025-08-26

Fast-VAT: Accelerating Cluster Tendency Visualization using Cython and Numba
MSR Avinash (Presidency University, Bangalore), Ismael Lachheb (EPITA School of Engineering,Computer Science, Paris, France)
https://arxiv.org/abs/2507.15904

Fast-VAT: Accelerating Cluster Tendency Visualization using Cython and Numba
Visual Assessment of Cluster Tendency (VAT) is a widely used unsupervised technique to assess the presence of cluster structure in unlabeled datasets. However, its standard implementation suffers from significant performance limitations due to its O(n^2) time complexity and inefficient memory usage. In this work, we present Fast-VAT, a high-performance reimplementation of the VAT algorithm in Python, augmented with Numba's Just-In-Time (JIT) compilation and Cython's static typing and low-level …

kh2d-solver: A Python Library for Idealized Two-Dimensional Incompressible Kelvin-Helmholtz Instability
Sandy H. S. Herho, Nurjanna J. Trilaksono, Faiz R. Fajary, Gandhi Napitupulu, Iwan P. Anwar, Faruq Khadami, Dasapta E. Irawan
https://arxiv.org/abs/2509.16080

kh2d-solver: A Python Library for Idealized Two-Dimensional Incompressible Kelvin-Helmholtz Instability
We present an open-source Python library for simulating two-dimensional incompressible Kelvin-Helmholtz instabilities in stratified shear flows. The solver employs a fractional-step projection method with spectral Poisson solution via Fast Sine Transform, achieving second-order spatial accuracy. Implementation leverages NumPy, SciPy, and Numba JIT compilation for efficient computation. Four canonical test cases explore Reynolds numbers 1000--5000 and Richardson numbers 0.1--0.3: classical shear…

Abmax: A JAX-based Agent-based Modeling Framework
Siddharth Chaturvedi, Ahmed El-Gazzar, Marcel van Gerven
https://arxiv.org/abs/2508.16508 https://arxiv.o…

Abmax: A JAX-based Agent-based Modeling Framework
Agent-based modeling (ABM) is a principal approach for studying complex systems. By decomposing a system into simpler, interacting agents, agent-based modeling (ABM) allows researchers to observe the emergence of complex phenomena. High-performance array computing libraries like JAX can help scale such computational models to a large number of agents by using automatic vectorization and just-in-time (JIT) compilation. One of the caveats of using JAX to achieve such scaling is that the shapes of…